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From the flow in Figure 5-10, we can see that the initial state of the managed heap includes five objects starting with Obj A at address 0x02000000. At a certain point, a platform invocation call to an asynchronous native API is required. Furthermore, the address of Obj C (0x02000090) needs to be passed to the API. Upon successfully calling the asynchronous native API, a garbage collection occurs causing Obj A and Obj B to be collected. This leaves a gap of two free objects on the managed heap and the garbage collector dutifully rectifies the problem by compacting the managed heap and therefore moving Obj C to address 0x02000000. It also coalesces the two free blocks and places them at the end of the heap. After the garbage collection has finished, the asynchronous API call we made earlier decides to write to the address initially passed to it (0x02000090), which originally held Obj C. As you can see, with the asynchronous API writing to that address, we will experience a managed heap corruption as the memory is no longer occupied by Obj C. Because the invocation of native code is such a common task, a solution had to be devised that allowed for safe invocation in light of a compacting garbage collector. The solution is called pinning and refers to the capability to pin specific objects on the managed heap. When an object is pinned, the garbage collector will not move the object for any reason until the object is unpinned. If Obj C in Figure 5-10 was pinned prior to invoking the asynchronous native API, the managed heap corruption would not have occurred due to the garbage collector not moving Obj C during the compaction phase. Let s take a look at an example of a simple application that performs pinning and see what it looks like in the debugger. Listing 5-6 shows the source code of the application. Listing 5-6 Sample application using pinning

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Many data modeling tools are available, everything from industry-standard tools (such as ERwin Data Modeler from Computer Associates or ER/ Studio from Embarcadero Technologies) to freeware tools. The features and functionality you need in a modeling tool extend beyond which notation it supports. Although it s not necessarily a part of the overall design process for a data model, choosing a data modeling tool can determine your level of success and frustration when it comes to creating a model. Here, we present a list of features that you should keep an eye out for when choosing a modeling tool. It is not meant to be an exhaustive list; rather, it is the list of must-haves for any data modeler to get the job done.

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The object in question appears to be a byte array with 50 elements, which also looks very similar to the byte array that we created in our application. Furthermore, because the do command is capable of displaying details of the object, the object s metadata seems to be structurally intact. Please note that the objsize command was used to get the total size (including members of the object) of the object (64). The next interesting piece of information to look at is the contents of the array itself. We can use the dd command to display the entire object in raw memory form:

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If we use varchar for attributes without considering the actual data, we could have data integrity problems. The main reason we use data types is to enforce data integrity. If we are storing a date, the datetime data type ensures that the entered information is a valid date. Storing a date in a varchar could lead to problems. For example, what if the application code has a glitch that omits the first / and writes the date as 35/2007 You might say, So what We can fix that with a script, but can you really fix it Take the date January 13, 2005, as an example. If that gets stored as 113/2005, you have a problem. It could be converted to 1/13/2005 or 11/3/2005. Had we used the datetime data type from the start, we would have received an error when the application wrote 113/2005, and the problem could have been found and fixed. There are literally hundreds of examples, but we think you get the point: Use the correct data type, and you are on your way to having solid data integrity.

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So far, we have discussed how objects live in managed heap segments divided into generations and how these objects are either garbage collected or promoted to the next generation, depending on if they are still referenced (or still rooted). One question that still remains is what it means for an object to be rooted. The next section introduces the notion of roots, which are at the heart of the decision-making process the GC uses to determine if an object can be collected.

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Data format This includes any requirements that a given type of data have a specific length, type of character, and specific order of characters. Examples include date and time formats, user name and password fields, and alphanumeric value constraints (e.g., no letters in a Social Security Number field). Data relationships and integrity Relationships that require the association of data from one entity with another are business rules in a data model. For example, all orders must be associated with a customer, or all outgoing shipments must have shipping details. Another example is the requirement that multiple records be updated if a single piece of information is changed for example, updating the ship date of a shipment automatically updates similar fields in order summary tables.